For many years, various brightfield, darkfield, and e-beam scanning methodologies have been used to inspect surfaces. These scanning technologies make use of radiation scattered, diffracted, and/or reflected (collectively referred to herein as scattered) by a surface to characterize and examine features of the surface. The details of these and other related scanning and inspection technologies are well known to those having ordinary skill in the art.
In many of these type inspection tools, an object (commonly, a wafer or reticle) is secured to a movable stage and then a light beam is projected onto the object. The stage is controllably moved to permit the surface of the object to be scanned. As the surface of the object is scanned, an appropriately positioned time delay integration (TDI) sensor detects the light scattered from the surface. The TDI sensor generates signals corresponding to the detected light. These signals are then processed using a variety of different methodologies to detect defects.
FIG. 1(a) illustrates one conventional implementation of a bright-field surface inspection tool. An inspection surface 101 is mounted on a movable stage 102 in readiness for inspection. A focusing element 104 is positioned to receive light from the inspection surface 101. The focusing element 104 focuses light from the inspection surface 101 and forms a magnified image of the inspection surface 101, which is received by a TDI sensor 105. FIG. 1(b) schematically depicts the field of view 110 for the focusing element 104. The portion of the image surface 105′ imaged by the TDI sensor 105 is also depicted.
Referring again to FIG. 1(a), as the inspection surface 101 is scanned (for example along a y-axis, depicted by arrow 103), images are taken along a portion of the inspection surface. This portion of the inspection surface is referred to as a strip. As an inspection surface is scanned, a portion of the inspection surface as wide as the TDI sensor is scanned. By scanning adjacent strips of the surface, the entire inspection surface can be scanned. FIG. 1(c) depicts one scanning pattern used for scanning an inspection surface 101. A plurality of such strips 120 are scanned until images are collected for the entire inspection surface 101. The circled area 121 depicts a section of a scanned portion of the inspection surface 101.
FIG. 1(d) is an expanded view of the area defined by circled area 121 of FIG. 1(c). In conventional implementations, the strips 120 are scanned in a carefully aligned non-overlapping manner such that the maximum area of the inspection surface 101 can be scanned in a minimum time. The width of the inspection surface 101 scanned by the strips 120 is determined by a variety of factors including, but not limited to TDI sensor size, system magnification, system resolution, as well as a number of other factors known to persons having ordinary skill in the art.
FIG. 2(a) depicts one type of TDI sensor 105 used in conventional inspection tools. The depicted sensor 105 comprises an array of photo sensor elements formed on a single chip. The circled portion 202 is depicted again in the expanded view of FIG. 2(b). In one conventional inspection system, the TDI sensor 105 comprises an array of charge coupled device (CCD) photo sensor elements 203. The photosensor elements 203 are used to generate image pixels. In one implementation, a TDI sensor 105 comprising an array of 2048×512 photosensor elements 203 can be used. In the depicted implementation, each photosensor element 203 is about 13μ (micron) by 13μ in size. Therefore, a the active region of a typical TDI sensor 105 is about 27 mm by 7 mm in size. Such TDI sensors typically have data rates in the hundreds (or thousands) of mega pixels per second (MPPS).
When coupled with the focusing element (e.g., 104 of FIG. 1(a)), the TDI sensor 105 can be used to create magnified images of an inspection surface. Typical inspection surfaces include images of mask reticles or semiconductor wafers as well as other surfaces. Using conventional inspection tools, the focusing element typically magnifies the inspection surface by about 100×. Using the previously described TDI sensor 105, under 100× magnification, each photosensor element 203 images a portion of the surface about 0.13μ square.
The resolving power of optical inspection tools can be characterized by the “point-spread-function” (PSF) of the tool. The PSF is affected by a number of factors including, but not limited to the optical quality of the lenses (or other optical elements) used in the focusing element, the wavelength of light, the NA of the lenses in the focusing element, as well as other factors.
In a conventional bright field inspection tool, the PSF can be depicted as shown in FIG. 3(a). FIG. 3(a) is a one-dimensional depiction of a typical PSF 301 plotted with respect to measured light intensity I. The distance between the two central minima 302 and 303 of the PSF 301 is defined as the spot size S. In order to obtain optical sensitivity commensurate with the optical resolution of the system an adequate number of image pixels must be used to span the spot size S. Where there are too few pixels per spot size S, the resulting images are said to be under-sampled. Such under-sampled images have reduced optical quality and have lower signal-to-noise ratios (SNR). Conversely, to achieve high sensitivity, a system designer ordinarily increases the optical magnification of the system or decreases the size of the photosensor elements of the TDI sensor arrays in order to achieve an adequate number of image pixels per spot size S. In order to obtain a desired sensitivity in a conventional inspection system there must be enough pixels per spot size to capture the full optical resolution possible with the system. Thus, in conventional systems, the system designer is faced with a difficult problem. He can, at high total system speed, generate images with an inadequate sampling ratio (too few pixels per PSF) resulting in images with relatively low SNR and/or decreased contrast. Alternatively, the sampling ratio can be increased (e.g., by increasing the optical magnification or decreasing the size of the photosensor elements in the TDI array) to better sample the optical image and thus improve the overall system sensitivity and signal to noise ratio. But, by increasing sampling ratio, the system is slowed down because an increasing the number of pixels must be processed. Moreover, an increased amount of time must be dedicated to acquiring these pixels. Additionally, increasing system magnification can be a very expensive proposition. Therefore, the designer is faced with a difficult tradeoff between system sensitivity and system throughput.
In conventional systems, a reasonable design compromise has been found using pixelization ratios (sampling ratios) of at least 2.5:1. This is shown in FIG. 3(b), which depicts a PSF 311 in one dimension. The depicted PSF 311 has a pixelization ratio of 2.5 image pixels per spot size S of the point spread function 311. PSF's digitized at pixelization ratios of less than 2.5 image pixels per spot size S are said to be under-sampled. In such conditions, small pixel to spot alignment differences between digitized images result in increased noise and lower system sensitivity. Thus, in conventional inspection tools, under-sampling typically results in dramatically reduced performance.
Although existing inspection machines and processes accomplish their designed purposes reasonably well, they have some limitations. There is a need for higher throughput and greater sensitivity than is currently provided by existing machines and processes. For these and other reasons, improved surface inspection tools and methodologies are needed.